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CTMC模型的企业热线话务信道的预测
连续时间马尔可夫链模型 客服热线 话务信道 信道预测 系统占线率
2022/3/23
为了减少用户接通客服热线电话的等待时间，同时控制企业在客服热线方面的投入成本，结合用户行为，基于企业数据，采用连续时间马尔可夫链(continuoustimeMarkovchain，CTMC)的数学模型对企业热线话务进行信道预测分析，寻求影响信道需求的相关参数。对不同规模企业的话务进行仿真，比对在不同客户量、不同通话保持时间需求、不同通话频率条件下的成功通话率、阻塞通话率及系统占线率，实现一种企业...
基于LSTM模型的恐怖袭击事件发生时间预测
恐怖袭击事件 预测 长短时记忆 神经网络
2022/3/25
针对部分地区恐怖袭击短期内频发的问题，提出了基于长短时记忆（LSTM）神经网络模型的恐怖袭击事件发生时间预测方法。首先，建立了恐怖袭击事件演化模型，对局部地区存在的恐怖袭击事件短期内数量剧增现象进行了分析。其次，以演化模型为基础从全球恐怖主义数据库（GTD）中提取出17项代表恐怖袭击事件特性的指标，并构建了用于预测的LSTM模型。采用伊拉克2001年9月至2016年底的恐怖袭击事件数据进行实验分析...
Direct Regression Modelling of High-order Moments in Big Data
Big data Higher-order moment U-statistics Estimating equation Divide-and-conquer
2016/1/26
Big data problems present great challenges to statisti-cal analyses, especially from the computational side. In this paper, we consider regression estimation of high-order mo-ments in big data problem...
Evaluation of somatic copy number estimation tools for whole-exome sequencing data
CNV prediction Somatic alterations The Cancer Genome Atlas CNV algorithms
2016/1/26
Evaluation of somatic copy number estimation tools for whole-exome sequencing data.
Estimating Spatial Autocorrelation with Sampled Network Data
NetworkDataAnalysis Paired Maximum Likelihood Estimator
2016/1/26
Spatial autocorrelation is a parameter of importance for network data analysis. To estimate spatial autocorrelation, maximum likelihood has been popularly used. However, its rigorous implementation re...
Boundary Harnack principle and gradient estimates for fractional Laplacian perturbed by non-local operators
Harmonic function boundary Harnack principle gradient estimate non-local operator Green function Poisson kernel
2016/1/26
Boundary Harnack principle and gradient estimates for fractional Laplacian perturbed by non-local operators.
Testing the Diagonality of a Large Covariance Matrix in a Regression Setting
Bias-Corrected Test Covariance Diagonality Test High Di- mensional Data
2016/1/26
In multivariate analysis, the covariance matrix associated with a set of vari-ables of interest (namely response variables) commonly contains valuable infor-mation about the dataset. When the dimensio...
When do emotionally exhausted employees speak up? Exploring the potential curvilinear relationship between emotional exhaustion and voice
emotional exhaustion prohibitive voice promotive voice job security
2016/1/26
Two studies were conducted to address the potential nonlinear relationship between emotional exhaustion and voice. Study 1 developed and tested a model rooted in conservation of resources theory in wh...
Copula function’s concentration set and its concentrated partition
Copula function local correlation structure concentration set concentration measure
2016/1/25
The research on the local correlation structure of copula function is an attractive topic.This paper investigates bivariate copula function’s local correlation structure by defining its concentration ...
Band Width Selection for High Dimensional Covariance Matrix Estimation
Bandable covariance Banding estimator Large p, small n Ratio- consistency Tapering estimator Thresholding estimator
2016/1/25
The banding estimator of Bickel and Levina (2008a) and its tapering version of Cai, Zhang and Zhou (2010), are important high dimensional covariance esti-mators. Both estimators require choosing a ban...
On Smoothing Estimation For Seasonal Times Series With Long Cycles
Large deviation Large p, small n Optimal detection boundary Sparse signal Thresholding Weak dependence
2016/1/25
We consider two alternative tests to the Higher Criticism test of Donoho and Jin (2004) for high dimensional means under the spar-sity of the non-zero means for sub-Gaussian distributed data with unkn...
Optimal Reinsurance under Distortion Risk Measures
Distortion risk measure expected premium principle the optimal reinsurance strategy VaR TVaR
2016/1/25
In this paper, we discuss the optimal reinsurance strategy of minimizing the in-surer’s risk under the distortion risk measure. We assume that reinsurance premium is determined by the expected premium...
Testing Covariates in High Dimensional Regression
Generalized Linear Model High Dimensional Data Hypothe- ses Testing
2016/1/25
In a high dimensional linear regression model, we propose a new procedure for testing statistical significance of a subset of regression coefficients. Specifically,we employ the partial covariances be...
Maximum-Likelihood Estimation For Diffusion Processes Via Closed-Form Density Expansions
asymptotic expansion diffusion discrete observation maximum-likelihood estimation transition density
2016/1/25
This paper proposes a widely applicable method of approximate maximum-likelihood estimation for multivariate diffusion process from discretely sampled data. A closed-form asymptotic expansion for tran...
Preconditioning is a technique from numerical linear algebra that can accelerate algorithms to solve systems of equations. In this pa-per, we demonstrate how preconditioning can circumvent a stringent...